Base Station Association Research Articles

Joint Downlink Base Station Association and Power Control for Max-Min Fairness: Computation and Complexity

In a heterogeneous network (HetNet) with a large number of low power base stations (BSs), proper user-BS association and power control is crucial to achieving desirable system performance. In this paper, we systematically study the joint BS association and power allocation problem for a downlink cellular network under the max-min fairness criterion. First, we show that this problem is NP-hard. Second, we show that the upper bound of the optimal value can be easily computed, and propose a two-stage algorithm to find a high-quality suboptimal solution. Simulation results show that the proposed algorithm is near-optimal in the high-SNR regime. Third, we show that the problem under some additional mild assumptions can be solved to global optima in polynomial time by a semi-distributed algorithm. This result is based on a transformation of the original problem to an assignment problem with gains $\log(g_{ij})$, where $\{g_{ij}\}$ are the channel gains.

A Markov Decision Process (MDP) based Load Balancing Algorithm for Multi-cell Networks with Multi-carriers

Conventional mobile state (MS) and base station (BS) association based on average signal strength often results in imbalance of cell load which may require more powerful processor at BSs and degrades the perceived transmission rate of MSs. To deal with this problem, a Markov decision process (MDP) for load balancing in a multi-cell system with multi-carriers is formulated. To solve the problem, exploiting Sarsa algorithm of on-line learning type [12], α -controllable load balancing algorithm is proposed. It is designed to control tradeoff between the cell load deviation of BSs and the perceived transmission rates of MSs. We also propose an e-differential soft greedy policy for on-line learning which is proven to be asymptotically convergent to the optimal greedy policy under some condition. Simulation results verify that the α -controllable load balancing algorithm controls the behavior of the algorithm depending on the choice of α. It is shown to be very efficient in balancing cell loads of BSs with low α.

Downlink Performance of Cellular Systems With Base Station Sleeping, User Association, and Scheduling

Base station (BS) sleeping has emerged as a viable solution to enhance the overall network energy efficiency by inactivating the underutilized BSs. However, it affects the performance of users in sleeping cells depending on their BS association criteria, their channel conditions towards the active BSs, and scheduling criteria and traffic loads at the active BSs. This paper characterizes the performance of cellular systems with BS sleeping by developing a systematic framework to derive the spectral efficiency and outage probability of downlink transmission to the sleeping cell users taking into account the aforementioned factors. In this context, we develop a user association scheme in which a typical user in a sleeping cell selects a BS with \textbf{M}aximum best-case \textbf{M}ean channel \textbf{A}ccess \textbf{P}robability (MMAP) which is calculated by all active BSs based on their existing traffic loads. We consider both greedy and round-robin schemes at active BSs for scheduling users in a channel. Once the association is performed, the exact access probability for a typical sleeping cell user and the statistics of its received signal and interference powers are derived to evaluate the spectral and energy efficiencies of transmission. For the sleeping cell users, we also consider the conventional \textbf{M}aximum \textbf{R}eceived \textbf{S}ignal \textbf{P}ower (MRSP)-based user association scheme along with greedy and round-robin schemes at the BSs. The impact of cell-zooming is incorporated in the derivations to analyze its feasibility in reducing the coverage holes created by BS sleeping. Numerical results show the trade-offs between spectral efficiency and energy efficiency in various network scenarios. The accuracy of the analysis is verified through Monte-Carlo simulations.

Distributed Pricing-Based User Association for Downlink Heterogeneous Cellular Networks

This paper considers optimization of the user and base-station (BS) association in a wireless downlink heterogeneous cellular network under the proportional fairness criterion. We first consider the case where each BS has a single antenna and transmits at fixed power and propose a distributed price update strategy for a pricing-based user association scheme, in which the users are assigned to the BS based on the value of a utility function minus a price. The proposed price update algorithm is based on a coordinate descent method for solving the dual of the network utility maximization problem and it has a rigorous performance guarantee. The main advantage of the proposed algorithm as compared to an existing subgradient method for price update is that the proposed algorithm is independent of parameter choices and can be implemented asynchronously. Further, this paper considers the joint user association and BS power control problem and proposes an iterative dual coordinate descent and the power optimization algorithm that significantly outperforms existing approaches. Finally, this paper considers the joint user association and BS beamforming problem for the case where the BSs are equipped with multiple antennas and spatially multiplex multiple users. We incorporate dual coordinate descent with the weighted minimum mean-squared error (WMMSE) algorithm and show that it achieves nearly the same performance as a computationally more complex benchmark algorithm (which applies the WMMSE algorithm on the entire network for BS association) while avoiding excessive BS handover.

Distributed Base Station Association and Power Control for Heterogeneous Cellular Networks

In this paper, we propose a universal joint base station (BS) association (BSA) and power control (PC) algorithm for heterogeneous cellular networks. Specifically, the proposed algorithm iteratively updates the BSA solution and the transmit power of each user. Here, the new transmit power level is expressed as a function of the power in the previous iteration, and this function is called the power update function (puf). We prove the convergence of this algorithm when the puf of the PC strategy satisfies the so-called “two-sided scalable (2.s.s.) function” property. Then, we develop a novel hybrid PC (HPC) scheme by using noncooperative game theory and prove that its corresponding puf is 2.s.s. Therefore, this HPC scheme can be employed in the proposed joint BSA and PC algorithm. We then devise an adaptation mechanism for the HPC algorithm so that it can support the signal-tointerference-plus-noise ratio (SINR) requirements of all users whenever possible while exploiting multiuser diversity to improve the system throughput. We show that the proposed HPC adaptation algorithm outperforms the well-known Foschini-Miljianic PC algorithm in both feasible and infeasible systems. In addition, we present the application of the developed framework to design a hybrid access scheme for two-tier macrocell-femtocell networks. Numerical results are then presented to illustrate the convergence of the proposed algorithms and their superior performance, compared with existing algorithms in the literature.

Energy Saving in Cellular Networks by Dynamic RS–BS Association and BS Switching

In this paper, we propose a dynamic scheme that reduces energy consumption in relay-assisted cellular networks by switching light-loaded base stations (BSs) into sleeping mode and by transferring the traffic load in these cells to neighboring cells using dynamic relay-station-BS (RS-BS) associations. We first investigate how to determine the RS-BS associations to guarantee the coverage when the BS modes are given. The problem is modeled as a generalized assignment problem (GAP) that is NP-hard, and a heuristic algorithm is then proposed. Based on the proposed RS-BS association algorithm, a tabu search approach, which finds the combination of BS modes, is presented. Simulation results show that our proposed scheme makes the active BS sets to dynamically change as the traffic load varies, and in the given scenario, the energy consumption of BSs can be reduced by nearly 40% when the traffic load is low.

Predictive Association Control for Frequent Handover Avoidance in Femtocell Networks

Appropriate base station association decisions in dense femtocell networks help to improve throughput while reducing frequent handovers of mobile stations. We consider the association control problem of mobile stations as an optimal control problem and obtain a rolling-out suboptimal control policy which is based on the predictive mobility of mobile stations. In addition, we derive a simple and lightweight online association control policy for each mobile station. The simulation results show that the proposed method provides large gain in both handover frequency and throughput over the current methods.

Joint Base Station Association and Power Control via Benders' Decomposition

Heterogeneous cellular network (Hetnets), where various classes of low power base stations (BS) are underlaid in a macro-cellular network, is a promising technique for future green communications. These new types of BSs can achieve substantial improvement in spectrum-efficiency and energy-efficiency via cell splitting. However, mobile stations perceive different channel gains to different base stations. Therefore, it is important to associate a mobile station with the right BS so as to achieve a good communication quality. Oftentimes, the already-challenging BS association problem is further complicated by the need of transmission power control, which is an essential component to manage co-channel interference in many wireless communications systems. Despite its importance, the joint BS association and power control (JBAPC) problem has remained largely unsolved, mainly due to its non-convex and combinatorial nature that makes the global optimal solution difficult to obtain. This paper aims to circumvent this difficulty by proposing a novel algorithm based on Benders' Decomposition to solve the non-convex JBAPC problem efficiently and optimally. In particular, we endeavor to maximize the system revenue and meanwhile associate every served mobile station with the right BS with the minimum total transmission power. We first propose a single-stage formulation that captures the two objectives simultaneously. The problem is then transformed in a way that can be efficiently solved using the proposed joint BS Association and poweR coNtrol algorithm (referred to as BARN) that is derived from classical Benders' Decomposition. Finally, we derive a closed-form analytical formula to characterize the effect of the termination criterion of the algorithm on the gap between the obtained solution and the optimal one. For practical implementation, we further propose an Accelerated BARN (A-BARN) algorithm that can significantly reduce the computational time. By carefully choosing the termination criterion, both BARN and A-BARN are guaranteed to converge to the global optimal solution.

Base station association schemes to reduce unnecessary handovers using location awareness in femtocell networks

In this paper, we propose a predictive scheme to generate reduced neighbor lists. In addition, we formulate a predictive association game. The game is designed to determine an optimal base station for maximum throughput and reduced handover frequency. Several simulation scenarios are set forth herein for analysis to show how our schemes improve performance in terms of throughput and handover frequency.

Base Station Association in Wireless Cellular Networks: An Emulation Based Approach

In order to utilize network resources efficiently and reduce regional congestion, associating mobile stations (MSs) with proper base stations (BSs) is of crucial importance in wireless cellular networks. There have been several load-aware proposals in literature, where most are classified into so-called closed-form approaches. In such approaches, each MS independently and deterministically selects the BS which is expected to provide the highest throughput. The throughput is estimated by a closed-form equation based on the assumption of the Proportional Fair (PF) user scheduler that ensures temporal fairness. However, the closed-form approaches do not perform well when the closed-form equation is not available, e.g., general α-fair user scheduler, where temporal fairness is not guaranteed, or deterministic BS association may make wrong decisions, e.g., under the dynamics of mobility or flow arrivals/departures. In this paper, we propose a novel BS association scheme, called ViSE (Virtual Scheduling based Emulation) to tackle such challenges. It emulates an optimal BS association by running a notion of virtual scheduler, and each MS randomly determines its associated BS with the probability proportional to the throughput virtually allocated by the virtual scheduler. We demonstrate through extensive simulations under various practical scenarios that ViSE outperforms the existing algorithms in terms of user schedulers with diverse fairness and robustness to network dynamics.

Adaptive Cooperation Switching for Multicell Downlink Using Statistical CSI

This letter proposes an adaptive scheme that switches between cooperative and non-cooperative transmission for multicell downlink systems in Kronecker spatially correlated channels, which exploits statistical channel state information (CSI). Based on the received signal-to-noise ratios (SNRs) and a cooperation metric, we propose a simple base station (BS) association method and then derive low-SNR capacity approximations for both cooperative and non-cooperative systems. Using the results, we provide a low-complexity efficient cooperation switching method to enhance the system capacity. Results show that the proposed method is more efficient than the conventional method to search the switching point.

Mechanism Design for Base Station Association and Resource Allocation in Downlink OFDMA Network

We consider a resource management problem in a multi-cell downlink OFDMA network whereby the goal is to find the optimal combination of (i) assignment of users to base stations and (ii) resource allocation strategies at each base station. Efficient resource management protocols must rely on users truthfully reporting privately held information such as downlink channel states. However, individual users can manipulate the resulting resource allocation (by misreporting their private information) if by doing so they can improve their payoff. Therefore, it is of interest to design efficient resource management protocols that are strategy-proof, i.e. it is in the users' best interests to truthfully report their private information. Unfortunately, we show that the implementation of any protocol that is efficient and strategy-proof is NP-hard. Thus, we propose a computationally tractable strategy-proof mechanism that is approximately efficient, i.e. the solution obtained yields at least 1/2 of the optimal throughput. Simulations are provided to illustrate the effectiveness of the proposed mechanism.

Roaming times of multi‐wireless systems for software defined radio

AbstractIn this paper, we evaluate the roaming time performance for a reconfigurable multi‐mode mobile station (MS) that experiences possible transition from one kind of wireless system standard to another. In future software defined radio systems (SDR) (IEEE Commun Mag 2000; 138–143, IEE 1998; 1–6, IEEE 1999; 1212–1216, IEEE Commun Mag 1995; 33), reconfigurability of the MS is achieved by downloading the system configuration software code over the wireless channel. For evaluation of the roaming times, a generalized state diagram of the multi‐mode MS is presented. We focus on evaluating the times for sensing the universal pilot channel, classic base station pilot channel, association and connection establishment signaling are included. We investigate the effects of packet successful transmission probability over the wireless channel. We also consider the effects of the system resource blocking probability, MS resource blocking probability, and signaling bit rate over the universal base station channel for different cases and design scenarios. Such evaluations are important for prior design of SDR mobile terminal and universal base station in global roaming situations. We include some analysis results from many obtained. These show the feasibility of wireless software download, and switching between different wireless standard as the mobile station roams. Copyright © 2003 John Wiley & Sons, Ltd.